
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x)))
(t_1 (* (* t_0 t_0) t_0))
(t_2 (* (* t_1 t_0) t_0)))
(*
(* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x))))
(+
(+ (+ t_0 (* (/ 1.0 2.0) t_1)) (* (/ 3.0 4.0) t_2))
(* (/ 15.0 8.0) (* (* t_2 t_0) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / sqrt(((double) M_PI))) * exp((fabs(x) * fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
public static double code(double x) {
double t_0 = 1.0 / Math.abs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / Math.sqrt(Math.PI)) * Math.exp((Math.abs(x) * Math.abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
def code(x): t_0 = 1.0 / math.fabs(x) t_1 = (t_0 * t_0) * t_0 t_2 = (t_1 * t_0) * t_0 return ((1.0 / math.sqrt(math.pi)) * math.exp((math.fabs(x) * math.fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)))
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = Float64(Float64(t_0 * t_0) * t_0) t_2 = Float64(Float64(t_1 * t_0) * t_0) return Float64(Float64(Float64(1.0 / sqrt(pi)) * exp(Float64(abs(x) * abs(x)))) * Float64(Float64(Float64(t_0 + Float64(Float64(1.0 / 2.0) * t_1)) + Float64(Float64(3.0 / 4.0) * t_2)) + Float64(Float64(15.0 / 8.0) * Float64(Float64(t_2 * t_0) * t_0)))) end
function tmp = code(x) t_0 = 1.0 / abs(x); t_1 = (t_0 * t_0) * t_0; t_2 = (t_1 * t_0) * t_0; tmp = ((1.0 / sqrt(pi)) * exp((abs(x) * abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0))); end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[(1.0 / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[Abs[x], $MachinePrecision] * N[Abs[x], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(t$95$0 + N[(N[(1.0 / 2.0), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(3.0 / 4.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(15.0 / 8.0), $MachinePrecision] * N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot t\_0\\
t_2 := \left(t\_1 \cdot t\_0\right) \cdot t\_0\\
\left(\frac{1}{\sqrt{\pi}} \cdot e^{\left|x\right| \cdot \left|x\right|}\right) \cdot \left(\left(\left(t\_0 + \frac{1}{2} \cdot t\_1\right) + \frac{3}{4} \cdot t\_2\right) + \frac{15}{8} \cdot \left(\left(t\_2 \cdot t\_0\right) \cdot t\_0\right)\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 12 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x)))
(t_1 (* (* t_0 t_0) t_0))
(t_2 (* (* t_1 t_0) t_0)))
(*
(* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x))))
(+
(+ (+ t_0 (* (/ 1.0 2.0) t_1)) (* (/ 3.0 4.0) t_2))
(* (/ 15.0 8.0) (* (* t_2 t_0) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / sqrt(((double) M_PI))) * exp((fabs(x) * fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
public static double code(double x) {
double t_0 = 1.0 / Math.abs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / Math.sqrt(Math.PI)) * Math.exp((Math.abs(x) * Math.abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
def code(x): t_0 = 1.0 / math.fabs(x) t_1 = (t_0 * t_0) * t_0 t_2 = (t_1 * t_0) * t_0 return ((1.0 / math.sqrt(math.pi)) * math.exp((math.fabs(x) * math.fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)))
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = Float64(Float64(t_0 * t_0) * t_0) t_2 = Float64(Float64(t_1 * t_0) * t_0) return Float64(Float64(Float64(1.0 / sqrt(pi)) * exp(Float64(abs(x) * abs(x)))) * Float64(Float64(Float64(t_0 + Float64(Float64(1.0 / 2.0) * t_1)) + Float64(Float64(3.0 / 4.0) * t_2)) + Float64(Float64(15.0 / 8.0) * Float64(Float64(t_2 * t_0) * t_0)))) end
function tmp = code(x) t_0 = 1.0 / abs(x); t_1 = (t_0 * t_0) * t_0; t_2 = (t_1 * t_0) * t_0; tmp = ((1.0 / sqrt(pi)) * exp((abs(x) * abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0))); end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[(1.0 / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[Abs[x], $MachinePrecision] * N[Abs[x], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(t$95$0 + N[(N[(1.0 / 2.0), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(3.0 / 4.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(15.0 / 8.0), $MachinePrecision] * N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot t\_0\\
t_2 := \left(t\_1 \cdot t\_0\right) \cdot t\_0\\
\left(\frac{1}{\sqrt{\pi}} \cdot e^{\left|x\right| \cdot \left|x\right|}\right) \cdot \left(\left(\left(t\_0 + \frac{1}{2} \cdot t\_1\right) + \frac{3}{4} \cdot t\_2\right) + \frac{15}{8} \cdot \left(\left(t\_2 \cdot t\_0\right) \cdot t\_0\right)\right)
\end{array}
\end{array}
(FPCore (x) :precision binary64 (* (sqrt (/ (pow (pow (exp x) 2.0) x) PI)) (+ (* 0.75 (pow x -5.0)) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (pow x 2.0))) x)))))
double code(double x) {
return sqrt((pow(pow(exp(x), 2.0), x) / ((double) M_PI))) * ((0.75 * pow(x, -5.0)) + fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / pow(x, 2.0))) / x)));
}
function code(x) return Float64(sqrt(Float64(((exp(x) ^ 2.0) ^ x) / pi)) * Float64(Float64(0.75 * (x ^ -5.0)) + fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / (x ^ 2.0))) / x)))) end
code[x_] := N[(N[Sqrt[N[(N[Power[N[Power[N[Exp[x], $MachinePrecision], 2.0], $MachinePrecision], x], $MachinePrecision] / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{{\left({\left(e^{x}\right)}^{2}\right)}^{x}}{\pi}} \cdot \left(0.75 \cdot {x}^{-5} + \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{{x}^{2}}}{x}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
fma-undefine99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
Taylor expanded in x around inf 99.9%
associate-*r/99.9%
metadata-eval99.9%
Simplified99.9%
pow-exp100.0%
sqr-pow100.0%
pow-prod-down100.0%
pow2100.0%
Applied egg-rr100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
sqrt-unprod100.0%
frac-times100.0%
pow-prod-up100.0%
add-log-exp100.0%
exp-sqrt100.0%
add-log-exp100.0%
exp-sqrt100.0%
log-prod100.0%
add-sqr-sqrt100.0%
add-log-exp100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
(FPCore (x) :precision binary64 (* (+ (* 0.75 (pow x -5.0)) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (pow x 2.0))) x))) (/ (pow (exp (* x 2.0)) (/ x 2.0)) (sqrt PI))))
double code(double x) {
return ((0.75 * pow(x, -5.0)) + fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / pow(x, 2.0))) / x))) * (pow(exp((x * 2.0)), (x / 2.0)) / sqrt(((double) M_PI)));
}
function code(x) return Float64(Float64(Float64(0.75 * (x ^ -5.0)) + fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / (x ^ 2.0))) / x))) * Float64((exp(Float64(x * 2.0)) ^ Float64(x / 2.0)) / sqrt(pi))) end
code[x_] := N[(N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[N[Exp[N[(x * 2.0), $MachinePrecision]], $MachinePrecision], N[(x / 2.0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(0.75 \cdot {x}^{-5} + \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{{x}^{2}}}{x}\right)\right) \cdot \frac{{\left(e^{x \cdot 2}\right)}^{\left(\frac{x}{2}\right)}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
fma-undefine99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
Taylor expanded in x around inf 99.9%
associate-*r/99.9%
metadata-eval99.9%
Simplified99.9%
pow-exp100.0%
sqr-pow100.0%
pow-prod-down100.0%
pow2100.0%
Applied egg-rr100.0%
pow-exp100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (+ (* 0.75 (pow x -5.0)) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (pow x 2.0))) x))) (/ (pow (exp x) x) (sqrt PI))))
double code(double x) {
return ((0.75 * pow(x, -5.0)) + fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / pow(x, 2.0))) / x))) * (pow(exp(x), x) / sqrt(((double) M_PI)));
}
function code(x) return Float64(Float64(Float64(0.75 * (x ^ -5.0)) + fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / (x ^ 2.0))) / x))) * Float64((exp(x) ^ x) / sqrt(pi))) end
code[x_] := N[(N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(0.75 \cdot {x}^{-5} + \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{{x}^{2}}}{x}\right)\right) \cdot \frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
fma-undefine99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
Taylor expanded in x around inf 99.9%
associate-*r/99.9%
metadata-eval99.9%
Simplified99.9%
pow-exp100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (+ (* 0.5 (pow x -3.0)) (/ (+ 1.0 (fma 0.75 (pow x -4.0) (* 1.875 (pow x -6.0)))) x))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * ((0.5 * pow(x, -3.0)) + ((1.0 + fma(0.75, pow(x, -4.0), (1.875 * pow(x, -6.0)))) / x));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(0.5 * (x ^ -3.0)) + Float64(Float64(1.0 + fma(0.75, (x ^ -4.0), Float64(1.875 * (x ^ -6.0)))) / x))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 + N[(0.75 * N[Power[x, -4.0], $MachinePrecision] + N[(1.875 * N[Power[x, -6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \left(0.5 \cdot {x}^{-3} + \frac{1 + \mathsf{fma}\left(0.75, {x}^{-4}, 1.875 \cdot {x}^{-6}\right)}{x}\right)
\end{array}
Initial program 99.9%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (* 0.75 (pow x -5.0)) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (* x x))) x)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * ((0.75 * pow(x, -5.0)) + fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / (x * x))) / x)));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(0.75 * (x ^ -5.0)) + fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / x)))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(0.75 \cdot {x}^{-5} + \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{x \cdot x}}{x}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
fma-undefine99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
Taylor expanded in x around inf 99.9%
associate-*r/99.9%
metadata-eval99.9%
Simplified99.9%
unpow299.9%
Applied egg-rr99.9%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (* 0.75 (pow x -5.0)) (fma 1.875 (pow x -7.0) (/ 1.0 x)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * ((0.75 * pow(x, -5.0)) + fma(1.875, pow(x, -7.0), (1.0 / x)));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(0.75 * (x ^ -5.0)) + fma(1.875, (x ^ -7.0), Float64(1.0 / x)))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(0.75 \cdot {x}^{-5} + \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1}{x}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
fma-undefine99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
Taylor expanded in x around inf 98.6%
(FPCore (x) :precision binary64 (/ (* (/ (exp (pow x 2.0)) (sqrt PI)) (/ (/ 0.5 x) x)) (fabs x)))
double code(double x) {
return ((exp(pow(x, 2.0)) / sqrt(((double) M_PI))) * ((0.5 / x) / x)) / fabs(x);
}
public static double code(double x) {
return ((Math.exp(Math.pow(x, 2.0)) / Math.sqrt(Math.PI)) * ((0.5 / x) / x)) / Math.abs(x);
}
def code(x): return ((math.exp(math.pow(x, 2.0)) / math.sqrt(math.pi)) * ((0.5 / x) / x)) / math.fabs(x)
function code(x) return Float64(Float64(Float64(exp((x ^ 2.0)) / sqrt(pi)) * Float64(Float64(0.5 / x) / x)) / abs(x)) end
function tmp = code(x) tmp = ((exp((x ^ 2.0)) / sqrt(pi)) * ((0.5 / x) / x)) / abs(x); end
code[x_] := N[(N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(0.5 / x), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{e^{{x}^{2}}}{\sqrt{\pi}} \cdot \frac{\frac{0.5}{x}}{x}}{\left|x\right|}
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 34.3%
associate-/r*36.2%
Simplified36.2%
associate-*r/49.9%
pow249.9%
div-inv49.9%
pow-flip51.9%
metadata-eval51.9%
Applied egg-rr51.9%
metadata-eval51.9%
pow-flip49.9%
div-inv49.9%
pow249.9%
associate-/r*52.3%
Applied egg-rr52.3%
(FPCore (x) :precision binary64 (* (/ (exp (pow x 2.0)) (sqrt PI)) (* 0.5 (/ (pow x -2.0) x))))
double code(double x) {
return (exp(pow(x, 2.0)) / sqrt(((double) M_PI))) * (0.5 * (pow(x, -2.0) / x));
}
public static double code(double x) {
return (Math.exp(Math.pow(x, 2.0)) / Math.sqrt(Math.PI)) * (0.5 * (Math.pow(x, -2.0) / x));
}
def code(x): return (math.exp(math.pow(x, 2.0)) / math.sqrt(math.pi)) * (0.5 * (math.pow(x, -2.0) / x))
function code(x) return Float64(Float64(exp((x ^ 2.0)) / sqrt(pi)) * Float64(0.5 * Float64((x ^ -2.0) / x))) end
function tmp = code(x) tmp = (exp((x ^ 2.0)) / sqrt(pi)) * (0.5 * ((x ^ -2.0) / x)); end
code[x_] := N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.5 * N[(N[Power[x, -2.0], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{{x}^{2}}}{\sqrt{\pi}} \cdot \left(0.5 \cdot \frac{{x}^{-2}}{x}\right)
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 34.3%
associate-/r*36.2%
Simplified36.2%
associate-*r/49.9%
pow249.9%
div-inv49.9%
pow-flip51.9%
metadata-eval51.9%
Applied egg-rr51.9%
div-inv51.9%
add-sqr-sqrt51.9%
fabs-sqr51.9%
add-sqr-sqrt51.9%
Applied egg-rr51.9%
associate-*l*36.2%
associate-*r/36.2%
*-rgt-identity36.2%
associate-*r/36.2%
Simplified36.2%
(FPCore (x) :precision binary64 (/ (* (exp (pow x 2.0)) (/ 0.5 (pow x 3.0))) (sqrt PI)))
double code(double x) {
return (exp(pow(x, 2.0)) * (0.5 / pow(x, 3.0))) / sqrt(((double) M_PI));
}
public static double code(double x) {
return (Math.exp(Math.pow(x, 2.0)) * (0.5 / Math.pow(x, 3.0))) / Math.sqrt(Math.PI);
}
def code(x): return (math.exp(math.pow(x, 2.0)) * (0.5 / math.pow(x, 3.0))) / math.sqrt(math.pi)
function code(x) return Float64(Float64(exp((x ^ 2.0)) * Float64(0.5 / (x ^ 3.0))) / sqrt(pi)) end
function tmp = code(x) tmp = (exp((x ^ 2.0)) * (0.5 / (x ^ 3.0))) / sqrt(pi); end
code[x_] := N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] * N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{{x}^{2}} \cdot \frac{0.5}{{x}^{3}}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 34.3%
associate-/r*36.2%
Simplified36.2%
associate-*r/49.9%
pow249.9%
div-inv49.9%
pow-flip51.9%
metadata-eval51.9%
Applied egg-rr51.9%
*-un-lft-identity51.9%
associate-/l*36.2%
add-sqr-sqrt36.2%
fabs-sqr36.2%
add-sqr-sqrt36.2%
metadata-eval36.2%
pow-flip36.2%
div-inv36.2%
add-sqr-sqrt36.2%
fabs-sqr36.2%
add-sqr-sqrt36.2%
associate-/l/34.3%
add-sqr-sqrt34.3%
fabs-sqr34.3%
add-sqr-sqrt34.3%
pow234.3%
cube-mult34.3%
Applied egg-rr34.3%
*-lft-identity34.3%
*-commutative34.3%
associate-*r/34.3%
Simplified34.3%
Final simplification34.3%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (/ 1.875 (pow x 7.0))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * (1.875 / pow(x, 7.0));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * (1.875 / Math.pow(x, 7.0));
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * (1.875 / math.pow(x, 7.0))
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(1.875 / (x ^ 7.0))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * (1.875 / (x ^ 7.0)); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{1.875}{{x}^{7}}
\end{array}
Initial program 99.9%
Simplified100.0%
expm1-log1p-u100.0%
expm1-undefine100.0%
Applied egg-rr100.0%
sub-neg100.0%
metadata-eval100.0%
+-commutative100.0%
log1p-undefine100.0%
rem-exp-log100.0%
associate-+r+100.0%
metadata-eval100.0%
Simplified100.0%
Taylor expanded in x around 0 15.9%
associate-/r*15.9%
add-sqr-sqrt15.9%
fabs-sqr15.9%
add-sqr-sqrt15.9%
*-un-lft-identity15.9%
Applied egg-rr15.9%
*-lft-identity15.9%
associate-/r*15.9%
pow-plus15.9%
metadata-eval15.9%
Simplified15.9%
(FPCore (x) :precision binary64 (* 0.5 (/ (pow x -3.0) (sqrt PI))))
double code(double x) {
return 0.5 * (pow(x, -3.0) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return 0.5 * (Math.pow(x, -3.0) / Math.sqrt(Math.PI));
}
def code(x): return 0.5 * (math.pow(x, -3.0) / math.sqrt(math.pi))
function code(x) return Float64(0.5 * Float64((x ^ -3.0) / sqrt(pi))) end
function tmp = code(x) tmp = 0.5 * ((x ^ -3.0) / sqrt(pi)); end
code[x_] := N[(0.5 * N[(N[Power[x, -3.0], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 \cdot \frac{{x}^{-3}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 2.0%
associate-*l/2.0%
*-lft-identity2.0%
associate-*r/2.0%
unpow22.0%
sqr-abs2.0%
unpow32.0%
Simplified2.0%
div-inv2.0%
inv-pow2.0%
sqrt-pow12.0%
metadata-eval2.0%
pow-flip2.0%
metadata-eval2.0%
Applied egg-rr2.0%
add-sqr-sqrt2.0%
sqrt-unprod2.0%
*-commutative2.0%
*-commutative2.0%
swap-sqr2.0%
pow-prod-down2.0%
sqr-abs2.0%
pow-prod-down2.0%
pow-sqr2.0%
metadata-eval2.0%
*-commutative2.0%
metadata-eval2.0%
sqrt-pow12.0%
inv-pow2.0%
Applied egg-rr2.0%
associate-*l/2.0%
metadata-eval2.0%
Simplified2.0%
*-un-lft-identity2.0%
sqrt-prod2.0%
sqrt-pow12.0%
metadata-eval2.0%
sqrt-div2.0%
metadata-eval2.0%
Applied egg-rr2.0%
*-lft-identity2.0%
*-commutative2.0%
associate-*l/2.0%
associate-/l*2.0%
Simplified2.0%
(FPCore (x) :precision binary64 (sqrt (* (pow x -6.0) (/ 0.25 PI))))
double code(double x) {
return sqrt((pow(x, -6.0) * (0.25 / ((double) M_PI))));
}
public static double code(double x) {
return Math.sqrt((Math.pow(x, -6.0) * (0.25 / Math.PI)));
}
def code(x): return math.sqrt((math.pow(x, -6.0) * (0.25 / math.pi)))
function code(x) return sqrt(Float64((x ^ -6.0) * Float64(0.25 / pi))) end
function tmp = code(x) tmp = sqrt(((x ^ -6.0) * (0.25 / pi))); end
code[x_] := N[Sqrt[N[(N[Power[x, -6.0], $MachinePrecision] * N[(0.25 / Pi), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{{x}^{-6} \cdot \frac{0.25}{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 2.0%
associate-*l/2.0%
*-lft-identity2.0%
associate-*r/2.0%
unpow22.0%
sqr-abs2.0%
unpow32.0%
Simplified2.0%
div-inv2.0%
inv-pow2.0%
sqrt-pow12.0%
metadata-eval2.0%
pow-flip2.0%
metadata-eval2.0%
Applied egg-rr2.0%
add-sqr-sqrt2.0%
sqrt-unprod2.0%
*-commutative2.0%
*-commutative2.0%
swap-sqr2.0%
pow-prod-down2.0%
sqr-abs2.0%
pow-prod-down2.0%
pow-sqr2.0%
metadata-eval2.0%
*-commutative2.0%
metadata-eval2.0%
sqrt-pow12.0%
inv-pow2.0%
Applied egg-rr2.0%
associate-*l/2.0%
metadata-eval2.0%
Simplified2.0%
herbie shell --seed 2024191
(FPCore (x)
:name "Jmat.Real.erfi, branch x greater than or equal to 5"
:precision binary64
:pre (>= x 0.5)
(* (* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x)))) (+ (+ (+ (/ 1.0 (fabs x)) (* (/ 1.0 2.0) (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))))) (* (/ 3.0 4.0) (* (* (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))))) (* (/ 15.0 8.0) (* (* (* (* (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x)))))))